Sentinel-2 and
Sentinel-3
Mission
Overview and
Status
Craig Donlon – Sentinel-3 Mission Scientist and Ferran Gascon – Sentinel-2 QC manager and others @ESA IOCCG-21, Santa Monica, USA 1-3rd March 2016
Overview
– What is Copernicus?
– Sentinel-2 mission and status
– Sentinel-3 mission and status
Sentinel-3A OLCI first light Svalbard: 29 Feb 14:07:45-14:09:45 UTC Bands 4, 6 and 7 (of 21) at 490, 560, 620 nm
Spain and Gibraltar 1 March 10:32:48-10:34:48 UTC
California USA 29 Feb 17:44:54-17:46:54 UTC
What is Copernicus?
6
Space Component
In-Situ Data
Services Component
A European response to global needs
What is Copernicus? – Space in Action for You!
• A source of information for policymakers,
industry, scientists, business and the
public
• A European response to global issues:
• manage the environment;
• understand and to mitigate the
effects of climate change;
• ensure civil security
• A user-driven programme of services for
environment and security
• An integrated Earth Observation system
(combining space-based and in-situ data
with Earth System Models)
Components & Competences
Services Component
Space Component
Overall Programme Coordination
Coordinators: Partners:
Service operators
EMCWF
Mercator Ocean
EEA
JRC
EUSC
EMSA snd
FRONTEX
Industries Private
companies
National Space
Agencies
In-situ data are supporting the Space and Services Components
Copernicus Funding
~€ 3.7 B
(from ESA and EU)
~€ 3 B for space
€ 2.3 B
by ESA
€ 0.8 B
by EU (FP7, GIO and Grant)
~€ 0.7 B
for services
Funding for Development Phase until 2013 (c.e.c.):
Funding for Operational Phase as from 2014 (c.e.c.):
€ 4.3 B for the whole programme
(from EU)
Space Component funding (ESA’s entrusted tasks)
€ 3.1 B
Planned Sentinel Schedule
Etna slopes
sentinel-2
Sentinel-2 Mission Overview
• Spacecraft: 2 operating in twin configuration
• Orbit: Sun-synchronous at 786 km (14+3/10 revs per day), with LTDN 10:30 AM
• MultiSpectral Instrument (MSI): operating in pushbroom principle, filter based optical system
• Spectral bands: 13 (VIS–NIR–SWIR spectral domains)
• Spatial resolution: 10m / 20m / 60m
• Swath: 290 km
Sentinel-2 A/B/C/D
Sentinel-2 Second Generation A/B
Sentinel-2 swath & coverage
SPOT5 60 x 60 km2
IRS P6 LISS III 141x141 km2
Landsat ETM+ 180 x 172 km2
High revisit time (5 days at equator) assured by twin satellite observations performed over a very large swath
Geographical Coverage:
• All land masses 56° S bis 83° N incl. major
islands All EU Islands < 20 km off the coast
• All Mediterranean
• Inland waters and all closed seas
Sentinel-2 290 x 290 km2 !!
Satellite and Instrument
• Filter based push broom imager (280 kg, 1 m3)
• Three mirrors silicon carbide telescope, with dichroic beam splitter
• Focal plane arrays: Si CMOS VNIR detectors, HgCdTe SWIR detectors.
• Onboard wavelet compression (divided by 3)
• Integrated video & compression electronics (state of the art wavelet compression)
• Radiometric resolution 12bits
• Daily generated telemetry: 1.4 TB
• Satellite mass: 1200 kg
• Satellite power consumption: 1250 W
• Hydrazine propulsion system (120 kg - including provision for safe mode, debris avoidance and EOL orbit decrease for faster re-entry)
• Accurate AOCS based on multi-head Star Tracker and fiber optic gyro
• X band mission data distribution (520 Mbits/sec)
• Mission data onboard storage: 2.4 Tbits
Satellite MultiSpectral instrument
• Multispectral Instrument: pushbroom with 13 bands in the VNIR and SWIR
• High spatial resolution: 10m, 20m and 60m;
• Wide field of view: 290 km • Duty cycle: average 17 min/orbit, maximum 32 min/orbit • Lifetime: 7.25 years, extendable to 12 years
Sentinel-2 Mission Highlights
• 2 Satellites in twin formation,
• Sun-synchronous orbit at 786 km (14+3/10 revs/day), with LTDN 10:30 AM
• Revisit: 5 days at equator (with 2 satellites) under same viewing conditions;
Sentinel-2A Launch last night!
June 23rd 2015
Name High-level Description Production Preservation Strategy
Volume
Level-1B Top-of-atmophere radiances in sensor
geometry
Systematic Long-term ˜27 MB (each 25x23km2)
Level-1C Top-of-atmosphere reflectances in cartographic
geometry
Systematic Long-term ˜500 MB (each 100x100km2)
Level-2A Bottom-of-atmosphere reflectances in cartographic
geometry (prototype product)
On user side* (using
Sentinel-2 Toolbox**)
N/A ˜600 MB (each 100x100km2)
Sentinel-2 Products
*: The possibility of a systematic global production of L2A is currently being explored. **: https://sentinel.esa.int/web/sentinel/toolboxes/sentinel-2
Level-1C / Algorithm
Level-0 Level-0 Consolidated Level-1A Level-1B Level-1C
TELEMETRY ANALYSIS
PRELIMINARY QUICK-LOOK AND CLOUD
MASK GENERATION
DECOMPESSION
SWIR PIXELS REARRANGEMENT
RADIOMETRIC CORRECTIONS
- Inv. on-board equalization,- Dark signal correction,- Blind pixels removal,- Cross-talk correction,- Relative response correction,- Defective/no-data correction,- Deconvolution/Denoising,- Binning of 60m bands.
GEOMETRIC VIEWING MODEL REFINEMENT
- Refining of the viewing model using a global set of reference images,- Registration between VNIR and SWIR focal planes (optional).
RESAMPLING
- Geometry interpolation grid computation,- Resampling (B-splines).
CONVERSION TO REFLECTANCES
PREVIEW IMAGE AND MASKS GENERATION
(defective pixels, cloud & land/water)
algorithms developed in cooperation with
S2 assumption on coastal acquisitions 20 km offshore 280 km swath – lots of data.
https://sentinels.copernicus.eu/web/sentinel/missions/sentinel-2/acquisition-plans
Products Qualification On-going
data quality report on-line athttps://sentinels.copernicus.eu/documents/247904/685
211/Sentinel-2+Data+Quality+Report
Absolute geolocation performances (without geometric refinement) measured over 17 test sites.
Measurements in line with requirements.
Level-1 Products Pre-Qualification
Multi-spectral registration performances measured show that the mean circular error over all band couples and detectors is lower than 0.23 pixel of the coarser band.
Level-1 Products Pre-Qualification
Signal-to-Noise Ratio (SNR) calculated from images of the MSI sun diffuser.
Measured SNR values largely exceeding requirements.
Level-1 Products Pre-Qualification
REQUIREMENTS
S2-MPC RESULTS
SNR@Lref Lref SNR Margin
Band/Unit - W/m2/Sr/μm - %
B01 129 129.0 1016,50 688
B02 154 128.0 201,90 31
B03 168 128.0 228,60 36
B04 142 108.0 214,50 51
B05 117 74.5 238,50 104
B06 89 68.0 206,10 132
B07 105 67.0 208,80 99
B08 174 103.0 208,10 20
B8A 72 52.5 153,10 113
B09 114 9.0 164,70 44
San Francisco Bay
Coastal Monitoring
Algae bloom, Baltic Sea
Venice
breakwater
surface effects
boats
Copernicus Sentinel data 2015, RBINS processing
Courtesy K. Ruddick, D. V.d. Zande, RBINS
Coral Reefs Monitoring
London Wind Turbine Array (E. Channel)
(Quinten Vanhellemont & Kevin Ruddick, RBINS)
490nm native 10m resolution Hartog/Dorre Island, West Australia
Sentinel–3 Mission Overview
Optical Mission Payload
providing
Sea and land color data,
through OLCI (Ocean and
Land Color Instrument)
Sea and land surface
temperature, through the
SLSTR (Sea and Land
Surface Temperature
Radiometer)
• Operational mission in high-inclination, low Earth orbit
• Full performance achieved with 2 satellites in orbit (S-3A,-3B)
In addition, the payload design
will allow
Data continuity of the Vegetation
instrument (on SPOT4/5),
Enhanced fire monitoring
capabilities
Topography Mission Payload
providing
Sea surface topography data,
through a Topo P/L including a Ku-/C-
band Synthetic Aperture Radar
Altimeter (SRAL), a bi-frequency
MicroWave Radiometer (MWR), and
a Precise Orbit Determination
(POD) including
GNSS Receiver
DORIS
Laser Retro-Reflector
Sentinel-3a launch from Plesetsk Cosmodrome 16th February 2016
Sentinel-3a launch from Plesetsk Cosmodrome 16th February 2016
(Credit: Antero Isola)
Sentinel-3: Satellite Orbit details
S3B has a 180° phase separation on the same orbital plane
1 Repeat Cycle
(27 days)
2 days
Ground Track Patterns
S3-A S3-B
Instrument Swath Patterns
1400 km SLSTR (nadir)
740 km SLSTR (oblique)
1270 km OLCI
SRAL (>2 km) and MWR (20 km)
nadir track
SRAL tracks at the equator:
S3A = 104 km track separation
S3A+B = 52 km separation
SRAL orbit drivers:
• Ground track repeatability,
• Dense spatial sampling
Orbit control requirement:
• Ground track dead-band ±1km
Orbit type
Repeat cycle
LTDN
Average altitude
Inclination
Repeating frozen SSO
27 days (14 + 7/27 orbits/day)
10:00
815 km
98.65°
Sentinel-3 Optical Coverage (2 satellites with 180° phase separation)
OLCI mean revisit time
with 2 satellites
SLSTR nadir-view mean revisit time
with 2 satellites
0.5
2.0
1.0
0.2
Days
Days
S3 OLCI: Technical details
Basic configuration similar to MERIS:
• 5 Camera Optical Sub Assemblies (COSA),
• 5 Focal Plane Assemblies (FPA),
• 5 Video Acquisition Modules (VAM),
• 1 Scrambling Window Assembly (SWA),
• 1 OLCI Electronic Unit (OEU) managing all the instrument functions,
• 1 calibration assembly allowing radiometric and spectral calibration.
Optical layout
Ocean and Land Colour Imager
Compared to MERIS:
• 100% overlap with SLSTR
• More spectral bands (from 15 to 21): 400-1020 nm
• Broader swath: 1270 km
• Full res. 300m acquired systematically for land & ocean
• Improved characterization, e.g. straylight, camera boundary characterization
• Timeliness: 3 hours NRT Level 2 product
Reduced sun glint by camera tilt in west (12.6°)
MERIS Bands λ center Width
Yellow substanace/detrital pigments
412.5 10
Chl. Abs. Max 442.5 10
Chl & other pigments 490 10
Susp. Sediments, red tide 510 10
Chl. Abs. Min 560 10
Suspended sediment 620 10
Chl. Abs, Chl. fluorescence 665 10
Chl. fluorescence peak 681.25 7.5
Chl. fluorescence ref., Atm. Corr. 708.75 10
Vegetation, clouds 753.75 7.5
O2 R-branch abs. 761.25 2.5
O2 P-branch abs. 778.75 15
Atm corr 865 20
Vegetation, H2O vap. Ref. 885 10
H2O vap., Land 900 10
New OLCI bands λ center Width
Aerosol, in-water property 400 15
Fluorescence retrieval 673.75 7.5
Atmospheric parameter 764.375 3.75
Cloud top pressure 767.5 2.5
Atmos./aerosol correction 940 20
Atmos./aerosol correction 1020 40
Multi-sensor time series
Band Set of OLCI in the Visible and the Near Infra-Red
• Higher spectral resolution than all previous sensors: Important for atmospheric correction, complex coastal waters, phytoplankton types
• Consistency with MERIS: facilitates merging (no need to do band-shifting to establish inter-sensor biases)
(After S. Sathyendranath)
55
5
65
9
86
5
SLSTR
Sentinel-3 OLCI Basic Geometry
1270 km
~09:00 LST ~10:30 LST 10:00 LST
FWHM for Oa21 will not be 40nm but 23nm due to optical transmission and detector response. Note, SNR performance remains compliant with large margins. (SNR EoL prediction: 197 vs Spec: 152)
SRD
CDR
(Pelloquin, C. and J. Nieke. 2012, OLCI and SLSTR simulated spectral response function, S3 Calval WS, Oct-2012)
OLCI Normalized Spectral Response
Functions
Same behavior as for MERIS
https://sentinels.copernicus.eu/web/sentinel/technical-guides/sentinel-3-olci/olci-instrument/spectral-response-function-data
OLCI instrument and camera
test & characterisation sequence
S3A-OLCI NEdL and SNR
0
500
1000
1500
2000
1.E-03
1.E-02
1.E-01
1.E+00
1.E+01
1.E+02
1.E+03
350 450 550 650 750 850 950 1050
SNR[-]
L,NEDL[W.m
-².sr-1.µm
-1]
Wavelength[nm]
Lref
NeDLTypical
SNRtypical
S3A-OLCI* SNR shows excellent consistency of intra-camera (different spectral bands, spectra or full and reduced resolution modes), and inter-camera measurements. A good correlation between the test results and the SNR model was established
*Measurements made prior to swap of cameras in June 2015. We expect similar performance for the Flight Model.
SN
R
OLCI: UV exposure and Hemi-reflectance stability (S3-RP-CSL-OLCI-09035)
OLCI and SLSTR diffuser material
OLCI and SLSTR diffuser material:
• Same material for OLCI and SLSTR flat
panel diffusers
• Zenith Polymer®, an optical PTFE
• Produced by SphereOptics/ElringKlinger AG,
Germany
• Production process according to “Space-
Grade conditions” i.e., cleanness is closely
monitored (e.g., PTFE raw material (powder)
bake out at 24hrs, <1mbar, 95deg)
• Environmental conditions (thermal cycling,
UV exposure, Radiation, ageing) were
verified in a delta-qualification.
• Strict contamination control during AIV.
• All values are within requirements and
within budget. Estimated total duration of sun illumination for OLCI diffusers over mission lifetime
OLCI spectral calibration
3 absorption peaks are proposed for nominal spectral calibration
Erbium-doped
Zenith 8%
« pink diffuser »
40 50 60 70 80 90
100
350 450 550 650 750 850 950 1050 1150 Wavelength (nm)
Refl
ecti
vit
y (
%)
Peak @409 nm
40
50
60
70
80
90
100
400 404 408 412 416 420 Wavelength (nm)
Refl
ecti
vit
y (
%)
Peak @ 522 nm
30 40 50 60 70 80 90
100
515 520 525 530 535 Wavelength (nm)
Refl
ecti
vit
y (
%)
Peak @ 800 nm
30 40 50 60 70 80 90
100
790 795 800 805 810 Wavelength (nm)
Refl
ecti
vit
y (
%)
3 other peaks optional: 490 nm, 658 nm, 975 nm. MERIS absorption bands
Within OLCI a maximum of 3 peaks each with 15 spectral lines can be used.
Better Characterisation than for MERIS
In addition, sample core products will be released to all users as early as possible for familiarisation
today
Core products availability
Data provided to commissioning phase teams
Reference sets of core products released to validation team/ expert users
Level 1 pre-qualified core product release. Gradual ramp-up of operations and progressive release of level 2 pre-qualified core products
ESA & EUMETSAT SHARE OPERATIONS
EU Copernicus Regulation: full, open and free data policy, defining responsibilities for ESA and EUMETSAT and overall financial envelope
Dedicated EU-ESA and EU-EUMETSAT Copernicus agreements
Operational Core Products - full technical documentation at https://sentinel.esa.int
– The operational core products description (including ATBD) is available at:
http://sentinel.esa.int
Open and Free data access policy
https://sentinels.copernicus.eu https://scihub.copernicus.eu/
Sentinel Data – Online Access
– ESA Data Hub Software (DHuS) provides an open source Web Interface
– Users can set scripts to automatically download data
Online data access at: scihub.copernicus.eu
52
Scientific Toolboxes Sentinel 3 Toolbox
Sentinel-3 Toolbox:
• Visualisation & processing of Sentinel-3 OLCI and SLSTR
data and other optical data
• Uncertainty visualization and exploitation
• Remote in-situ database access
• Synergistic use of OLCI and SLSTR
• Various OLCI and SLSTR data processors
http://step.esa.int/
Application Modes
PC, notebook, tablet
I Interactive Exploration
SNAP gpt:_
SNAP Engine
II
PC, notebook server
bulk / NRT processing
cluster, cloud
III EO data
processing centre
SNAP gpt:_
SNAP Engine:_
IV Cloud Exploitation
Platform
PC, notebook, tablet
ESA Sentinel Satellite Smartphone App
Important Dates: Deadline for abstract submission 16 October 2015 Notification of Acceptances End January 2016 Issue of Preliminary Programme February 2016 Opening of Registration February 2016 Release of the Final Programme at the symposium Submission of Full Papers at the symposium
Themes: Atmosphere, Oceanography, Cryosphere, Land, Hazards, Climate and Meteorology, Solid Earth/Geodesy, Near-Earth Environment, Methodologies and Products, Open Science 2.0
http://lps16.esa.int
PRAGUE 09-13 MAY 2016
Main Objective: Presentation of Exploitation Results based on ESA Earth Observation Measurements
Sentinel-3 Toolbox
• Ingesting Sentinel-3 OLCI and SLSTR
• Ingesting MERIS, AATSR, ATSR, MODIS, SeaWiFS, VIIRS, Proba-V, SPOT-VGT, Landsat TM, etc.
• Basic functions: band maths, statistical analysis, spectrum analysis, geometric tools …
• Uncertainty information exploitation
– OLCI and SLSTR error variables
– Various visualisation modes (blending and overlays)
– Propagation build into band-maths (Standard Combined Uncertainty, GUM 95)
• Remote in-situ database access tool (MERMAID for MERIS/OLCI)
• OLCI / SLSTR / SYN Data Processors
– OLCI/SLSTR collocation tool
– Pixel classification (cloud screening)
– Atmospheric correction and in-water processing (FLH-MCI, C2R, CoastColour, FuB,..)
– SST & LST processing
– Land thematic processing (fAPAR)
• Commissioning phase support tools
– OLCI/SLSTR collocation accuracy assessment (L1C product)
– SLSTR PDU stitching tool
A study to improve the retrieval of water products in extreme scattering and absorbing coastal (and inland) waters, focus on S3 (primarily) and S2
ESA SEOM - Case2 Extreme Waters
?
?
?
?
? ?
?
Problems to be addressed: • Atmospheric correction in turbid
waters
• CHL retrieval in high non-algae
particle as well asd high CDOM
loaded waters
• Identification of water conditions,
and selection of appropriate
algorithm(s) for extreme ranges
of water constituent
concentrations
• Large variability of SIOPs
Relevance/Applications: Water quality, Primary Production and C fixation, sediment transport, dredging +
dumping, organic C from rivers, eutrophication, Rrver engineering
Team:
Approach Radiative transfer simulations, in-situ data from selected extreme water sites
Atmospheric correction
• comparing & improving three different approaches (C2RCC - NN, polymer, NIR/SWIR)
• exploiting new bands of S3 (O-400nm, O-1020nm, SLSTR-SWIR)
• study applicability to S2 MSI
In-water algorithms
• comparing & adapting candidate algorithms (spectrum inversion, semi-analytical, regression)
• exploiting O-400nm band for absorbing waters and O-1020nm band for scattering
Prototyping and validation
• match-ups and decorrelation analysis
• list of demonstration sites, linked to local PIs
• S3 OLCI & SLSTR in 2016
Link with international activities: IOCCG WGs, international science support team, ESA OC CCI, GEO Comm. Practice, …
Duration: April 2015 – March 2017
C2X Project:
Marine Primary Production:
Model Parameters from Space
(MAPPS)
T.Jackson, H.Bouman, S.Sathyendranath, T.Platt, F.Melin
contributors and details available at
www.global-maps.org/data New database on
photosynthesis irradiance
parameters from across the
globe, which will be
published and made
accessible through ESSD.
Inter-model comparison and model
improvement and optimisation
Objective: improve estimates of Marine Primary Production through the production of
remote-sensing data based estimates of phytoplankton photosynthesis-
irradiance parameters.
Global satellite products of photosynthesis-
irradiance parameters
Demonstration products should be available soon
Example of model at SST of 22oC SST CHL PAR
Objective: produce an uncertainty-characterised, inter-sensor bias-corrected, merged time series of ocean-colour products for climate research, and engage with users
V2 of the merged time series (SeaWiFS, MERIS and MODIS-A) released in March 2015.
Specific aims of this version 2.0 release:
• improves the in situ database used for uncertainty characterisation
• optimizes the uncertainty generation for the CCI data
• improves consistency in many areas, including unifying the binning/mapping processing
• improves bias correction, able to respond to temporal variation (primarily seasonal)
• incorporates an improved cloud mask for MERIS
• benefits from a more automated quality assurance process
• extends the time series to the end of 2013
• refreshes the input datasets to the latest versions
Relative error in V2 Chl based on bias. Red vertical line: GCOS requirement for accuracy
May 2010 bias, log_10 Chl
May 2010 RMSD, log_10 Chl
Ocean-Colour Component of ESA’s Climate Change Initiative
OC-CCI: Improved coverage in many under-sampled regions
OC-CCI:Future Plans
• Incorporate VIIRS into the time series
• Extend time series to 2015+
• Prepare for Sentinel-3 • Improve Case-2
products
Acknowledgements ESA and OC-CCI thank the many members of the ocean-colour community who helped in many ways: validation data, participation in user consultation; feedback on products. A special thanks to NASA for their continued help and support.
Match-up in situ observations, per optical class
Bias in log_10 chlorophyll, per optical class
RMSD in log_10 chlorophyll, per optical class
OC-CCI: Improved uncertainty characterisation in V2 compared with V1
800
400
0
Processing step Version 1 Version 2
Input datasets
Latest versions available prior to release in 2013
Latest versions available prior to release in 2015
Atmospheric correction
MERIS: POLYMER V2
MERIS: Improved POLYMER V3
In situ database Initial version Extended version with substantial increase in match-ups with satellite data
Binning
Beam Binner for MERIS; L2Gen for SeaWiFS and MODIS- A
Beam Binner for all sensors, improving consistency in this step
Bias correction Static correction per pixel Improved bias correction; accounts for seasonal variation in bias
Cloud masking
Initial version of Idepix used for MERIS; : L2gen for SeaWiFS and MODIS-A
Improved cloud mask (Idepix 2.0) for MERIS; no change for SeaWiFS and MODIS-A: L2gen
Uncertainty generation
Underlying optical classification based on in situ database on Rrs
Optical classification custom generated for OC-CCI Version 2 satellite data
Uncertainty characterisation
Based on initial optical classification and initial in situ database
Benefited from OC-CCI-data-based optical classification, and improved in situ database
Quality Assurance Initial version, less automated More automated quality assurance process
Time series Sep 1997 to Dec 2012 Sep 1997 to Dec 2013
OC-CCI: Second version released in early 2015
Version 3 scheduled for release imminently
OC-CCI: Work continues
In situ database Match-up validation Uncertainty characterisation
Trends
Data assimilation into ecosystem models
Pools of Carbon in the Ocean Project: Rationale
• At the interface between marine ecosystem and climate models and Earth Observation is the carbon-to-chlorophyll ratio, which is a highly variable quantity.
• In 2010, GEO produced a “Carbon Strategy Report”. In response, the CEOS produced a document on “Carbon from Space” (CEOS, 2014). Both GEO and CEOS Reports highlight the importance of carbon products.
Main focus of POCO: Particulate Pools
• Total Particulate Carbon
• Particulate Organic Carbon
• Phytoplankton Carbon
Bigger pool Smaller pool
Measure-ments more difficult
More data Less data
Objectives • explore the potential of remote sensing for detecting particulate
carbon pools in the ocean • compare with models • focus on climate studies
Scientific Achievements: • Algorithm selection: 10 Carbon
algorithms reviewed and assessed
• In situ database: ~36,000 POC data points assembled
• Model/carbon data interaction: Data assimilation and comparison of MIT model with EO
• Uncertainty quantification: ~3,600 POC match-up points
• Some initial sresults on this slide
Dutckiewitz et al . (2015)
POC (in situ) (mg m-3) PO
C S
tram
ski e
t al
. 20
08
(m
g m
-3)
Nu
mb
er o
f M
atch
-up
s
POC, In Situ Stramski et al. 2008
OC-CCI Chl-a mg m-3 POC Stramski et al. 2008 Behrenfeld et al. 2005 Sathyendranath et al. 2009
Phytoplankton Carbon mg m-3 Phytoplankton Carbon Mg m-3
Website: www.oceancarbon.net Twitter (@ESA_POCO)
Colour and Light in the ocean from Earth Observation (CLEO) workshop
6-8 Sep 2016 ESA /ESRIN Frascati, Italy
The workshop is sponsored through selected SEOM projects, including: • Pools of Carbon in the Ocean • Photosynthetically Active Radiation and
Primary Production • Extreme Case-2 Waters Additional partner projects of ESA are: • Marine Photosynthesis Parameters from
Space • Ocean Colour Climate Change Initiative • Synergistic Exploitation of Hyper-and
Multispectral Sentinel-Measurements to Determine Phytoplankton Functional Types
http://congrexprojects.com/2016-events/cleo Please participate and help make workshop a success
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